1. Field of the Invention
The present invention relates to methods for ascertaining a gradient of a data-based function model, in particular using a control module having a hardware unit, which is designed to calculate the data-based function model in a hard-wired way.
2. Description of the Related Art
Data-based function models may be provided for implementing function models in control units, in particular in engine control units for internal combustion engines. Data-based function models are also referred to as parameter-free models and may be prepared without specific inputs from training data, i.e., a set of training data points.
Control modules having a main computing unit and a separate model calculation unit for calculating data-based function models in a control unit are known from the related art. Thus, for example, the published German patent application document DE 10 2010 028 259 A1 describes a control unit having an additional logic circuit as a model calculation unit which is designed for calculating exponential functions to assist in carrying out Bayesian regression methods, which are required in particular for calculating Gaussian process models.
The model calculation unit is designed as a whole for carrying out mathematical processes for calculating the data-based function model based on parameters and supporting points or training data. In particular, the functions of the model calculation unit are implemented solely in hardware for efficient calculation of exponential and summation functions, so that it is made possible to calculate Gaussian process models at a higher computing speed than may be carried out in the software-controlled main computing unit.
For many applications, the calculation of function values of data-based function models in control units, in particular for internal combustion engines, is sufficient. However, applications are known in which a gradient of a data-based function model is necessary, in particular to calculate an inverse data-based function model therewith.